Effects of Ephedrine, Caffeine, and Their Combination on Muscular Endurance
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to investigate the effects of ingesting caffeine (C), ephedrine (E), and their combination on muscular endurance, using a double-blind, repeated measures design. METHODS: Ninety minutes after ingesting either C (4 mg x kg-1), E (0.8 mg x kg-1), a combination of C+E, or a placebo (P), 13 male subjects performed a weight-training circuit consisting of three supersets (SS), each SS consisting of leg press (at 80% of 1 RM to exhaustion) followed by bench press (at 70% 1-RM to exhaustion); 2 min of rest intervened between SS. RESULTS: The trials involving ephedrine ingestion (C+E and E), when compared with the nonephedrine trials (C and P), caused significant increases (P < 0.05) in the mean number of repetitions completed for both the leg-press and bench-press exercises but only during the first SS. During that first set, the mean number (+/-SD) of repetitions for leg press was 19 +/- 8, 16 +/- 7, 14 +/- 6, and 13 +/- 5 for the C+E, E, C, and P trials, respectively. The mean numbers of repetitions for the first set of bench-press exercise were 14 +/- 3, 13 +/- 3, 12 +/- 3, and 12 +/- 3 for the C+E, E, C, and P trials, respectively. As a result, the total weight lifted during all three sets was greater for the trials involving ephedrine ingestion. Systolic blood pressure before exercise was significantly increased with both ephedrine treatment trials when compared with the other trials (C+E = 156 +/- 29 mm Hg; E = 150 +/- 14; C = 141 +/- 16; P = 138 +/- 14). CONCLUSION: It was concluded that acute ingestion of C+E and E increases muscular endurance during the first set of traditional resistance-training exercise. The performance enhancement was attributed primarily to the effects of E; there was no additive effect of C.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".